The proposed study will examine the developmental relationship between childhood and adolescent substance use and risky sexual behaviors in young adulthood. The study seeks 1 year of support to conduct analyses using 9 waves of data from the Seattle Social Development Project (SSDP). The gender-balanced, multiethnic urban panel of 808 youths was constituted in 1985 when respondents entered the fifth grade. Youths in the panel were interviewed through age 21. Approximately 91 percent of the sample was present for at least seven of the nine data assessment waves. Data were collected on a wide range of measures of problem behaviors such as substance use, sexual behavior, and delinquency. Data were also collected on individual, family, school, peer, and community predictors of those problem behaviors. This study will examine the developmental relationship between childhood and adolescent substance use and risky sexual behavior in young adulthood. Specifically, this study will examine the developmental trajectories of childhood and adolescent substance use and their associations with risky sexual behavior in young adulthood using General Growth Mixture Modeling (GGMM). Further, the study will examine the extent to which childhood and adolescent substance use have unique effects on risky sexual behavior in young adulthood after controlling for early predictors of substance use and sexual behavior. In addition, possible developmental mechanisms that link substance use and risky sexual behavior will be explored. Gender and ethnic differences in the developmental relationship between substance use and risky sexual behavior will be addressed. Results from this study will inform STD/HIV prevention efforts for adolescents and young adults. Dr. Guo recently completed her dissertation on high risk sexual behavior and condom use. Currently she is working on the NIDA-funded SDRG study "Substance Use and the Transition to Adult Roles." Her knowledge of the theories and research on high risk sexual behavior and on substance use prevention, her statistical expertise in multivariate techniques such as structural equation modeling, missing data techniques, and multilevel modeling, combine to provide the balance of substantive and statistical skills required for the proposed study. The proposed study will allow her to establish a career in the field of prevention.